In:
Computational Intelligence and Neuroscience, Hindawi Limited, Vol. 2019 ( 2019-03-03), p. 1-10
Abstract:
At present, research on hesitant fuzzy operations and measures is based on equal length processing, and an equal length processing method will inevitably destroy the original data structure and change the data information. This is an urgent problem to be solved in the development of hesitant fuzzy sets. Aiming at solving this problem, this paper firstly defines a hesitant fuzzy entropy function as the measure of the degree of uncertainty of hesitant fuzzy information and then proposes the concept of hesitant fuzzy information feature vector. The hesitant fuzzy distance measure and similarity measure are studied based on the information feature vector. Finally, the hesitant fuzzy network clustering method based on similarity measure is given, and the effectiveness of our algorithm through a numerical example is illustrated.
Type of Medium:
Online Resource
ISSN:
1687-5265
,
1687-5273
DOI:
10.1155/2019/5370763
Language:
English
Publisher:
Hindawi Limited
Publication Date:
2019
detail.hit.zdb_id:
2388208-6
